By: Jake Smiths
Enterprises today are navigating a rapidly shifting landscape. Sensors on factory floors push out nonstop telemetry, software developers run increasingly complex workloads, and AI agents are beginning to act on behalf of both. Yet, most organizations still rely on fragmented infrastructure. There are different systems for real-time events, analytics, and experimentation. The result: complexity, inefficiency, and slow innovation.
Recognizing the urgency to modernize, Tiger Data, the creator of TimescaleDB and Agentic Postgres, has entered into a strategic collaboration agreement (SCA) with Amazon Web Services (AWS). The partnership aims to accelerate the delivery of a unified, Postgres-based infrastructure that can support developers, devices, and AI agents in a single cohesive architecture.
For Tiger Data, the timing is critical. Data infrastructure is under increasing strain as organizations demand systems that scale without abandoning familiar ecosystems. Developers want to stay within the Postgres environment they already trust. Devices, from wearables to industrial robotics, generate massive volumes of time-series and event data. As AI agents emerge as a new class of “user,” enterprises need infrastructure that enables safe experimentation at scale.
This is where the collaboration with AWS becomes pivotal.
Strengthening the Developer Experience through AWS
A major component of the SCA centers on deepening technical integrations with AWS services. Tiger Data already offers streamlined connections to Amazon Athena, Amazon Redshift, Amazon QuickSight, and Amazon SageMaker, giving developers the ability to query operational and analytics datasets through the same SQL interface.
The new agreement expands that footprint, giving enterprises more ways to deploy Tiger Data’s Postgres stack through the AWS Marketplace and supporting joint investments in technical enablement and customer success. It also builds on Tiger Data’s earlier integration with Amazon S3 Tables, enabling data to stream into Apache Iceberg within seconds using SQL and open standards.
“The future of data infrastructure isn’t about specialized systems for every workload,” said Ajay Kulkarni, CEO and co-founder of Tiger Data. “It’s about a unified infrastructure that handles what developers build, what devices generate, and what agents need to operate—all on Postgres. With AWS, we’re making that architecture real, with integrations that connect Postgres to the full AWS stack, and the performance that makes it production-ready at scale.”
Preparing for the Next Wave: AI Agents
One of the most forward-looking elements of the partnership is its focus on AI agents. As organizations deploy agents to test workflows, perform autonomous tasks, and evaluate models, they need environments that enable safe, instantaneous experimentation.
Tiger Data’s Agentic Postgres is built specifically for this purpose. With instant, zero-copy environments, agents can run parallel experiments without ever touching production systems, a major leap forward for enterprises exploring AI-driven automation.
A Unified Architecture for Operational Data
At the infrastructure level, Tiger Data’s Postgres platform is engineered to handle high-frequency, high-volume data from modern applications. It supports billions of writes, low-latency queries, and automatic compression. Coupled with AWS analytics tools, this architecture transforms raw operational data into actionable intelligence across machine learning pipelines, dashboards, and real-time decision-making systems.
Tiger Cloud is available through AWS Marketplace and powers more than 2,000 customers across IoT, Web3, and AI, extending these capabilities in a fully managed model. Users can explore the platform or sign up directly through Tiger Cloud.
A Converged Future for Data Infrastructure
The strategic collaboration between Tiger Data and AWS represents a broader shift in how enterprises think about data architecture. Rather than stitching together specialized systems, organizations are moving toward unified platforms that serve developers, devices, and AI agents simultaneously.
By deepening integrations and expanding the reach of Postgres across AWS analytics and AI services, the SCA lays the foundation for more flexible, scalable, and AI-ready infrastructure. In a world where the boundaries between operational systems, analytics, and autonomous agents are blurring rapidly, Tiger Data and AWS are offering a blueprint for the next decade of innovation.
